Spectrum Sensing Algorithm Based on Self-Supervised Contrast Learning

Spectrum Sensing Algorithm Based on Self-Supervised Contrast Learning

The traditional spectrum sensing algorithm based on deep learning requires a large number of labeled samples for model training, but it is difficult to obtain them in the actual sensing scene. This paper applies self-supervised contrast learning in order to solve this problem, and a spectrum sensing...

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Bibliographic Details
Main Authors: Xinyu Li, Zhijin Zhao, Yupei Zhang, Shilian Zheng, Shaogang Dai
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Electronics
Subjects:
cognitive radio
spectrum sensing
self-supervised contrast learning
data augmentation
limited data
Online Access:https://www.mdpi.com/2079-9292/12/6/1317

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https://www.mdpi.com/2079-9292/12/6/1317

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